基于堆栈式LSTM网络的通信辐射源个体识别

doi:10.3969/j.issn.1001-506X.2020.12.30

Abstract

Abstract:

For solving the problems of complicated preprocessing and difficult feature extraction for the existing communication emitter individual identification, an algorithm of emitter individual identification based on stacked long short-term memory (LSTM) network is proposed. The algorithm directly uses IQ time series signal to train the LSTM network for realizing efficient individual identification of communication emitter and avoiding complex signal preprocessing. In order to make the LSTM network more suitable for communication emitter individual identification, the three-layer LSTM network is used to extract the deep features of the communication emitter and the network parameters are optimized by experiments. Then the generalization of the algorithm for practical application is investigated experimentally, and results show that the algorithm obtains good effects on other emitter data sets. Finally, the algorithm is verified by experiments, and the results show that compared with the traditional algorithm, the identification accuracy of the algorithm can reach 98% when the number of samples is larger. And the algorithm is more simple, faster and more intelligent, which is suitable for engineering and practical application.

Key words: communication emitter individual identification, long short-term memory (LSTM), parameter optimization, generalization

CLC Number:

TP181

Zilong WU, Hong CHEN, Yingke LEI, Xin LI, Hao XIONG. Communication emitter individual identification based on stacked LSTM network[J]. Systems Engineering and Electronics, 2020, 42(12): 2915-2923.

Figures/Tables 17

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References 33

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电台	矩阵维度
电台Ⅰ	(2, 37 748 736)
电台Ⅱ	(2, 35 336 192)
电台Ⅲ	(2, 35 762 176)
电台Ⅳ	(2, 31 391 744)
电台Ⅴ	(2, 37 675 008)

学习率	迭代次数/次				识别准确率/%
学习率	1 499 850	1 499 900	1 499 950	1 500 000	识别准确率/%
0.000 01	0.973	0.984	0.973	0.957	95.7
0.000 1	0.977	0.984	0.981	0.973	97.3
0.001	0.606	0.633	0.547	0.629	62.9

数据集	识别准确率/%
超短波数据集	85.00
手持式电台数据集	100.00
本文数据集	97.86

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Communication emitter individual identification based on stacked LSTM network

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